#' Returns tibble with only necessary columns for aggregation.
#'
#' @param dataframe_to_derive_column_names A tibble based on which the necessary columns will be derived.
#' @param dataframe_to_modify A tibble that will be used for subsetting.
#' @param start index of the first column
#' @param end index of the last column
#' @return tibble only with columns between start and end indexes and an area column
derive_necessary_columns <- function(dataframe_to_derive_column_names, dataframe_to_modify, start, end){
  only_columns_for_chart <- dataframe_to_derive_column_names[,c(start:end, 85)] %>% names()

  final_dataframe <- dataframe_to_modify %>% select(all_of(only_columns_for_chart))
  return(final_dataframe)
}

#' Returns tibble aggregated by the chosen variable.
#'
#' @param dataset A tibble based on which the necessary columns will be derived.
#' @param start index of the first column
#' @param end index of the last column
#' @param aggregating_variable the grouping column
#' @return aggregated tibble
aggregate_method <- function(dataset, start, end, aggregating_variable){
  return(aggregate(dataset[,start:end], by = list(aggregating_variable),
                   FUN = mean, na.rm = TRUE))
}

#' Returns complete dataframe for a country, with the structure that is required by
#' by radarchart function from fmsb library.
#'
#' @param dataframe_1 First dataframe
#' @param dataframe_2 index of the first column
#' @param row_to_select index of the row to select from the final DataFrame
#' @param rowname_1 name of the first rowname
#' @param rowname_2 name of the second rowname
#' @return dataframe for the country
derive_dataframe_for_country <- function(dataframe_1, dataframe_2, row_to_select,
                                         rowname_1, rowname_2){
  colnames(dataframe_1) <- c("area", "Epidemics", "Floods", "Drought", "Wildfires", "Earthquakes",
                             "Terror attacks", "Domestic violence", "Economic crises", "Climate Change")
  colnames(dataframe_2) <- c("area", "Epidemics", "Floods", "Drought", "Wildfires", "Earthquakes",
                             "Terror attacks", "Domestic violence", "Economic crises", "Climate Change")
  df_to_return <- rbind(dataframe_1[row_to_select,], dataframe_2[row_to_select,])
  df_to_return <- df_to_return[,2:10]
  rownames(df_to_return) <- c(rowname_1, rowname_2)
  df_to_return <- rbind(rep(5,9) , rep(1,9) , df_to_return) #needed for creating radarchart successfully
  return(df_to_return)
}

#' Plots the radarchart based on the provided DataFrame, with the given title,
#' The labels in the legend correspond to legend_1 and legend_2.
#'
#' @param dataframe dataframe that is required by radarchart function from fmsb library.
#' @param title title to put on the chart
#' @param legend_1 legend for the first froup
#' @param legend_2 legend for the second group
#' @return dataframe for the country
graph_radar <- function(dataframe, title, legend_1, legend_2){
  graph <- radarchart(dataframe,
                      axistype = 1 ,
                      #customize the polygons
                      pcol = colors_border,
                      #pfcol = , # for filling the polygons
                      pty = 32,
                      plwd = 2,
                      plty = 1,
                      #customize the grid
                      cglcol = "grey",
                      cglty = 1,
                      axislabcol = "grey",
                      caxislabels = seq(1,5,1),
                      cglwd = 0.8,
                      #custom labels
                      vlcex = 0.9,
                      title = title)
  legend(x = 1.5, y = 1, legend = c(legend_1, legend_2),
         bty = "n", pch = 20 , col = colors_border, text.width = 2, cex = 0.8, pt.cex = 2)
}